In-Flight Aircraft Trajectory Optimization within Corridors Defined by Ensemble Weather Forecasts

Abstract

Today, each flight is filed as a static route not later than one hour before departure. From there on, changes of the lateral route initiated by the pilot are only possible with air traffic control clearance and in the minority. Thus, the initially optimized trajectory of the flight plan is flown, although the optimization may already be based upon outdated weather data at take-off. Global weather data as those modeled by the Global Forecast System do, however, contain hints on forecast uncertainties itself, which is quantified by considering so-called ensemble forecast data. In this study, the variability in these weather parameter uncertainties is analyzed, before the trajectory optimization model TOMATO is applied to single trajectories considering the previously quantified uncertainties. TOMATO generates, based on the set of input data as provided by the ensembles, a 3D corridor encasing all resulting optimized trajectories. Assuming that this corridor is filed in addition to the initial flight plan, the optimum trajectory can be updated even during flight, as soon as updated weather forecasts are available. In return and as a compromise, flights would have to stay within the corridor to provide planning stability for Air Traffic Management compared to full free in-flight optimization. Although the corridor restricts the re-optimized trajectory, fuel savings of up to 1.1 %, compared to the initially filed flight, could be shown.

Advanced Flight Planning and the Benefit of In-Flight Aircraft Trajectory Optimization

“…The second option poses a challenge for operators and for the trajectory optimization tool. Theoretically, we could already show a benefit of a frequently re-optimized lateral trajectory in terms of fuel costs by approximately 1% [14,15]. Note, after each weather update, the current aircraft position might not be optimal anymore.…”

“…During the flight planning phase, this optimum is nonpredictable due to the major influence of actual weather conditions, which are relatively erratic. Especially when considering the large time horizon of a long-haul flight (about five hours) the predictability of the real weather conditions state a challenge for all stakeholders in the Air Traffic Management (ATM) [14].…”

“…Global weather data services, e.g., the Global Forecast System (GFS) provide hourly weather forecasts and indicators of the reliability of the forecast in terms of so-called ensemble forecast data with different look-ahead times [14]. Often, the prediction accuracy of the one-hour forecast is within 3%, compared to the next six-hour modeled actual weather state [14]. For predictions of more than one hour ahead, the prediction error increases significantly and does not provide satisfying input data for trajectory optimization [15].…”

“…For predictions of more than one hour ahead, the prediction error increases significantly and does not provide satisfying input data for trajectory optimization [15]. The modeled state, in turn, describes the real atmospheric state with an accuracy of approximately 5% [14].…”

“…Thereby, for every hour of the cruise phase of the flight, the TOolchain for Multicriteria Aircraft Trajectory Optimization (TOMATO) [10,16] is applied to the dynamic input variables to re-optimize the trajectory, and the recently activated trajectory is recalculated with the new input variables to calculate the benefit of the re-optimization. TOMATO provides multi-criteria optimized 4D trajectories beginning at an arbitrary position along the trajectory [16,17], considering frequently updated input data sets [14] and, if desired, also the respective statistical accuracy as a frequency distribution [6,18].…”